Lattice-Gas Automata for the Navier-Stokes Equation
TL;DR: It is shown that a class of deterministic lattice gases with discrete Boolean elements simulates the Navier-Stokes equation, anc, and can be used to design simple, massively parallel computing machines.
Abstract: We show that a class of deterministic lattice gases with discrete Boolean elements simulates the Navier-Stokes equation, anc can be used to design simple, massively parallel computing machines.
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TL;DR: An overview of the lattice Boltzmann method, a parallel and efficient algorithm for simulating single-phase and multiphase fluid flows and for incorporating additional physical complexities, is presented.
Abstract: We present an overview of the lattice Boltzmann method (LBM), a parallel and efficient algorithm for simulating single-phase and multiphase fluid flows and for incorporating additional physical complexities. The LBM is especially useful for modeling complicated boundary conditions and multiphase interfaces. Recent extensions of this method are described, including simulations of fluid turbulence, suspension flows, and reaction diffusion systems.
6,565 citations
Cites methods from "Lattice-Gas Automata for the Navier..."
...In the seminal work of the lattice gas automaton method for two-dimensional hydrodynamics, Frisch et al (1986) recognized the importance of the symmetry of the lattice for the recovery of the Navier-Stokes equation; for the first time they obtained the correct Navier-Stokes equation starting from…...
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...The requirement for using the nine-velocity model, instead of the simpler five-velocity square lattice, comes from the consideration of lattice symmetry: the LBE cannot recover the correct Navier-Stokes equations unless sufficient lattice symmetry is guaranteed (Frisch et al 1986)....
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TL;DR: In this article, the Navier-Stokes equation is obtained from the kinetic BGK equation at the second-order approximation with a properly chosen equilibrium distribution, with a relaxation parameter that influences the stability of the new scheme.
Abstract: We propose the lattice BGK models, as an alternative to lattice gases or the lattice Boltzmann equation, to obtain an efficient numerical scheme for the simulation of fluid dynamics. With a properly chosen equilibrium distribution, the Navier-Stokes equation is obtained from the kinetic BGK equation at the second-order of approximation. Compared to lattice gases, the present model is noise-free, has Galileian invariance and a velocity-independent pressure. It involves a relaxation parameter that influences the stability of the new scheme. Numerical simulations are shown to confirm the speed of sound and the shear viscosity.
4,481 citations
Abstract: We present a novel method for simulating hydrodynamic phenomena. This particle-based method combines features from molecular dynamics and lattice-gas automata. It is shown theoretically as well as in simulations that a quantitative description of isothermal Navier-Stokes flow is obtained with relatively few particles. Computationally, the method is much faster than molecular dynamics, and the at same time it is much more flexible than lattice-gas automata schemes.
3,338 citations
TL;DR: This article considers the empirical data and then reviews the main approaches to modeling pedestrian and vehicle traffic, including microscopic (particle-based), mesoscopic (gas-kinetic), and macroscopic (fluid-dynamic) models.
Abstract: Since the subject of traffic dynamics has captured the interest of physicists, many surprising effects have been revealed and explained. Some of the questions now understood are the following: Why are vehicles sometimes stopped by ``phantom traffic jams'' even though drivers all like to drive fast? What are the mechanisms behind stop-and-go traffic? Why are there several different kinds of congestion, and how are they related? Why do most traffic jams occur considerably before the road capacity is reached? Can a temporary reduction in the volume of traffic cause a lasting traffic jam? Under which conditions can speed limits speed up traffic? Why do pedestrians moving in opposite directions normally organize into lanes, while similar systems ``freeze by heating''? All of these questions have been answered by applying and extending methods from statistical physics and nonlinear dynamics to self-driven many-particle systems. This article considers the empirical data and then reviews the main approaches to modeling pedestrian and vehicle traffic. These include microscopic (particle-based), mesoscopic (gas-kinetic), and macroscopic (fluid-dynamic) models. Attention is also paid to the formulation of a micro-macro link, to aspects of universality, and to other unifying concepts, such as a general modeling framework for self-driven many-particle systems, including spin systems. While the primary focus is upon vehicle and pedestrian traffic, applications to biological or socio-economic systems such as bacterial colonies, flocks of birds, panics, and stock market dynamics are touched upon as well.
3,117 citations
Cites background from "Lattice-Gas Automata for the Navier..."
...A), (ii) lattice gas automata (Frisch et al., 1986; Chen et al., 1991; Peng and Herrmann, 1994; Tan et al., 1995) or cellular automata (see Sec....
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TL;DR: In this paper, the authors derived the stochastic differential equations corresponding to the updating algorithm of Dissipative Particle Dynamics (DPD), and the corresponding Fokker-Planck equation.
Abstract: The stochastic differential equations corresponding to the updating algorithm of Dissipative Particle Dynamics (DPD), and the corresponding Fokker-Planck equation are derived. It is shown that a slight modification to the algorithm is required before the Gibbs distribution is recovered as the stationary solution to the Fokker-Planck equation. The temperature of the system is then directly related to the noise amplitude by means of a fluctuation-dissipation theorem. However, the correspondingly modified, discrete DPD algorithm is only found to obey these predictions if the length of the time step is sufficiently reduced. This indicates the importance of time discretisation in DPD.
2,502 citations